Agree 100% - but because all the doors were mostly in the hands of men they had to be the first. Thankfully they were not only wanting and able, but thoughtfully happy to do so. And now I help open doors. One even told me once that was how I could repay him, open doors and help good people in the industry make their way. And I have done that for women - and men.

(Generally anonymously as well - few have ever known I did it. Just like myself. Few have ever told me I just know they did.)

I do not think I addressed anything to any other woman other than the poster and the editor and previously I even stated she had a few valid points. However, I do not share your feelings about this post which reads to me as, "I am woman you must treat me special." which in its background is really a - men see how you offend me, see how you must change, see how bad you really are post. Here are the rules for you to follow.

Except as a woman, I don't want another woman outlining special rules and forced female inclusion for me as a woman - there is law for that - it should be the best person gets the job not best person as long as X% are women. I do not wish to wonder if my next opportunity was only because the men felt they had to add another woman. That is not good for men or women.

Also you should not assume anything about me, as you do not know me or a single thing about my life experience. Whatever sexist interactions I have had have been far outweighed by the positive, supportive ones with the majority of men in this industry who have encouraged and supported myself and my career for over 15 years. Every door that has been opened for me is because of a man in this industry and NOT by my asking. In fact, most of it has been done anonymously in the background. I do not think there is an issue saying that in my 15 years of experience that sexism has not a predominant issue with tech. My path has not been blocked by men. That grumpy programmer who talks down to you, he does it with everyone it is not because you are a girl. He thinks everyone is his inferior. If our tool is a hammer sooner or later we think every problem is a nail.

But most importantly - IMO if you want to change things the author's own quote from Patrick Stewart says it best

“People will not listen unless you are an old, white man, so I’m an old white man, and I will use that to help people who need it.” — Sir Patrick Stewart

Well in this industry we have a whole lot of Patrick Stewart who are very aware they are male, most are white and they are aware of that too and they are seemingly mostly aware that it is on them to make sure women are treated equally and I have seen them go far beyond what most would do to ensure that happens. Is it perfect? No. Is there room for improvement? Always. Do we need to keep wearing it like a badge on our shoulder while we give them no credit? I would say no.

From my POV - One, two even ten interactions that someone 'you' label sexist does not taint the whole apple which is made up of hundreds or thousands of people depending on where you slice it. And if you want those guys to keep helping, then they should not feel direct or indirect hostilities towards them because someone else did something wrong. In this situation, this poster apparently has that feeling of hostility.

Not saying there are not institutionalized sexism in industries (try being an executive in gaming and being female) and that there are not sexist actors - there always will be, but if the hope is 100% non-sexist well that is never going to happen and in this industry thankfully, most of the gatekeepers willingly open up the gate.

That is my opinion and that is my right to express. You don't have to agree however. Thank you for listening.

You are welcome and just if it were me - I might give him a break :) He is just getting started and has not had to refine his outrage yet into metered language.. I can kind of appreciate that! Thank you for your acceptance of what I wrote and your thoughtful expression.

I appreciate your willingness to hear critique, so will honor that and give you my thoughts.

Just three examples, as I think that makes the point. Please accept these as in intended, critique not attack.

Thoughts.So first you are starting by telling him his view are short-sighted?

"I do, however, take issue with some of the points you made; I think they're a bit short-sighted"

Then you are using phrases like

"just couldn't be farther from the truth"

he does not think it is, so you are telling him he has no right to the opinion he expressedthat your view is accurate his is not.

"The post wasn't written to convince women who don't feel oppressed that they actually are."

again telling him his thoughts are invalid- intent does not matter when you write no one knows intent it is not a conversation. Your words have power outside intent and so perception is key.

Note: I have a similar feeling about how this author has presented this piece and how criticism has been addresses. Just because you use big words from women's studies to invalidate dissent, does not make it any less unprofessional to do so. To invite controversy is to also allow dissenters into the debate, this post does not allow for this without devaluation of the posted thoughts and feelings.

These types of retorts and the author's are based on a subtle use of the adhominem logic fallacy and I find that it would be have been much better to address his and others concerns without prejudice and defense.

Maybe you would find out just why he felt these things about what was written and a good discussion would have emerged. I would also assume many men probably feel the same way. Though assuming is always dangerous, so I could be wrong. However, with the "no you are wrong we are right" approach discourages debate or discussion and promotes only the author's view. Which if you read through the comments, quite a few people have issue with.

Thank you for listening. I hope it was received in the spirit intended.

If you are just reading this and about to hit reply, first please read the above comments as the poster asked me to give them this critique.

I find this need of Moz to tell people they don't feel what they feel for the right reasons and have no right to their own feelings and thoughts on a very gender directed post very off-putting and will be rethinking my need to promote your site in further articles and presentations.

Appreciate your honesty and so you know we don't all feel that way. You can read my posts below, but just so you know that hostility you fear is my reason for having issue with posts like this. Not all man are sexists and "don't know" and it in this industry most are not. They have been extremely supportive overall. Thank you for sharing.

No I am saying the methodology used means the sample size is too small and the sampling method too un-reliable (not replicable) to be considered applicable to anything, but the population studied. This is just statistics.

Ok I am out. Thank you. If you read all the studies posted, these things are all explained.

Nothing against Moz, but their research is snowball sampled and limited in number, so I put more trust in broad applicability and validity across geographies in the research and analysis run by Pew, Harvard and the other institutes whose academic departments are represented in the articles above and have long histories of replicable study.

You have to know how to interpret those, so I posted 4 articles that explain that and how in tech it is either 93 cents to the dollar or equal depending on what research you use. However the govt study is all persons, in all jobs, independent of skill or time off.It is a ie. a lumped study without regressive analysis that equals variability.

Read all the articles and you will find out what is wrong with that as a metric of ALL persons.

Yes I am familiar with the issues of sexism and racism (though racism seems to be a bit of a strawman in this discussion). However, I have a undergraduate in Sociology and am ABD with a PhD in the same, so these are not new topics to me ie I know the subject matter intimately from a personal and academic point of view.

So that being said I still contend it is a conflation of sexism with sexists. You can have acts of sexism without having institutionalized sexism. And not taking away from any personal experiences you might have had as when it rains every day where I live I may assume all places are rainy. However, if seen from the birdseye view that this is not the case, you might find the areas around to be sunny. This is the same.

If we want to just look at some facts here, in technology when you remove taking years off for children bearing and raising; tech salaries meter out at about 98 cents to the dollar female to male. Is it exact, no, but is it pretty darn close. Yes. So do we have room to improve, of course. However, If sexism were rampant in the technology industry this would not be the case. To add, tech companies such as Google provide 5 months of paid leave for women who have children to take as they see fit and other companies allow people to donate their days to help further eliminate this gap.

You may not agree with me, but I do not want conferences to pick women to meet a quota. I want to know I earned it and I have done just that. I earned my writing gigs, my speaking gigs, my place and my hopeful respect among peers. The men have been almost universally supportive and are the most supportive of any industry I have been in. If you are not experiencing the same you might look at the whys of this whether place, timing or internal issues.

And I am not a single minority, I know many women who have the same feeling I do about these issues. To me I believe there is an assumption of sexism where it is more likely a dispersion of sexists. This is like assuming you are in a jungle because you see a lion. You might just be at the zoo.

As for you telling me I am derailing the issue because I think women do better when they embrace the men in their lives who are breaking stereotypes and who care so deeply about women's issues is an attack I would expect.

However, just because you do not agree does not mean I am wrong. In my view, if you create a hostile approach even the kindest of people eventually give up. So yes. I find it male bashing to asses our industry as having institutionalized sexism as I know conference owners such as Rand (MOZ), Brett Tabke (Pubcon), Kristjan Mar Hauksson (RIMC), Marcus Tandler (SEOktoberFest), Danny Sullivan (SMX), and Matt McGowan (Former SES and SEW) have all made concerted efforts to make sure women get fair and equal treatment. So your assessment of this in such a negative light I find is counter productive and potentially damaging.

Are there always things to work on? yes! Do we get there by shaming men and pointing out just the bad and negatives? I think no. For instance when was the last article about all the men who have been so helpful in forwarding women in this industry. I don't think I have seen one yet. When is someone going to write that article?

While there are some valid points in the article, as a woman in tech since 1998, who has developed websites for everyone from Reba McIntire to Superpages to USA.gov. Who has spoken at Pubcon/SMX/SWSXi/RIMC and countless other non-industry based conferences. Who has written for SEW for 3 years as one of their top authors and last year was invited to SEOktoberfest; I take great issue with articles like these that put this amount of oneness on men and the perceived need for female protectionism. I think they make us women sound weak and in this industry every break was given to me by a male without my request. And though sexist men exist anywhere you go in this world there is not an inherent sexism issue here (in my experience). Other fields most certainly, but not in this one.

In fact, IMO the male bashing needs to stop as it will eventually become a barrier for men wanting to continue to help the way they have in the past. And they have most certainly helped, defended, backed, promoted and come to my aid throughout my career. Not all men, of course not, but most I have met. They are often my biggest cheerleaders and I believe credit is due as I know and have watched them do the same for other women.

However, I have expressed my views on multiple sites, so those that know me know mine and I am not in the mindset this very early morning to write a properly thought out post at this time and again. That being said I think Sugar Rae's article about the conference "issue" says it much more eloquently than I am able to at this time. So leave you with that

First this type of analysis requires the use of a null hypothesis. Which I do not see here. You cannot use r to simply prove an assumption correct. You must be testing again something, not inductively proofing.

Next, Pearson's r must meet the following criteria (below) and the data points are typically shown in scatter graphs around a line of best fit. This is not what is shown here. Here is a standard plot graph.

Here I am not seeing that #4 or #5 were accounted for also find showing the line of best fit without data unusual (outliers). Controlling for outliers in a Pearson's r is very important and if not controlled for other statistical measures would be more accurate.

Finally, using bar graphs to show a person's coefficient is unusual given the need to show data around a line of best fit.

In addition, if comparing the three networks you would most likely need to jump to a linear regression analysis were the variables are held at a constant to control for spurious relationships. At the least you must convert your r for comparison

And lastly I see no data on the tests for statistical significance here which if not run means you cannot be sure what the Pearsons r means. If a .5, but the statistical sig tests come back inconclusive you have no relationship.

You also do not show the r2 which tells you the coefficient of determination which gives you the ability to say yes a relationship is indeed causal. It is not sufficient to just compare r.

NOTE I am not saying you did not account for these, but would like to see how they were accounted for and if it is here and I missed it I apologize in advance.

Thank you!

Pearson's r REFERENCE

There are four assumptions that are made with respect to Pearson's correlation:

The variables must be either interval or ratio measurements (see our Types of Variable guide for further details).

The variables must be approximately normally distributed (see our Testing for Normality guide for further details).

There is a linear relationship between the two variables. We discuss this later in this guide (jump to this section here).

Outliers are either kept to a minimum or are removed entirely. We also discuss this later in this guide (jump to this section here).

There is homoscedasticity of the data. This is discussed later in this guide (jump to this section here).

From https://statistics.laerd.com/statistical-guides/pearson-correlation-coefficient-statistical-guide-2.php

Can you establish cause-and-effect?

No, the Pearson correlation cannot determine a cause-and-effect
relationship. It can only establish the strength of the association
between two variables. As stated earlier, it does not even distinguish
between independent and dependent variables.

How do I report the output of a Pearson product-moment correlation?

You need to state that you used the Pearson product-moment correlation and report the value of the correlation coefficient, r, as well as the degrees of freedom (df). You should express the result as follows:

where the degrees of freedom (df) is the number of data points minus 2 (N - 2). If you have not tested the significance of the correlation then leave that section out of the results.

Can I determine whether the association is statistically significant?

Yes, the easy way to do this is through a statistical programme, such
as SPSS. We provide a guide on how to do this, which you can find here.
You need to be careful how you interpret the statistical significance
of a correlation. If your correlation coefficient has been determined to
be statistically significant this does not mean that you have a strong
association. It simply tests the null hypothesis that there is no
relationship. By rejecting the null hypothesis you accept the
alternative hypothesis that states that there is a relationship but with
no information about the strength of the relationship or its
importance.

What is the Coefficient of Determination?

The coefficient of determination, r2, is the square of the Pearson correlation coefficient r (i.e. r2).
So, for example, a Pearson correlation coefficient of 0.6 would result
in a coefficient of determination of 0.62, which is 0.36. Therefore, r2
= 0.36. The coefficient of determination, with respect to correlation,
is the proportion of the variance that is shared by both variables. It
gives a measure of the amount of variation that can be explained by the
model (the correlation is the model). It is sometimes expressed as a
percentage (for example, 36% instead of 0.36) when we discuss the
proportion of variance explained by the correlation. However, we must
never write r2 = 36%, or any other percentage. We must always write it as a proportion, e.g. r2 = 0.36.

Thank you for your post today. As a white hat SEO, I do not look down at the gray or black (though craphat is a whole nother story). I know they have their reasons for doing so, but my personal choice and the one that works very well for me is using all white hat techniques. I make sure that everything I do is spot on from the code I write, the content we add, to the link building I have a partner do. I know when I do this my rankings stay stable and my clients are happy. However, this all takes time and I am constantly competing against fraudulent services that get rank fast, but lose it as quickly (probably just after the check clears ;))So it is nice to hear someone express their experience. I also really appreciate the tips!! And the Google News is a great idea! SO thank you!

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